Functionally diverging molecular quasi-speciesevolve by crossing two enzymesLars O. Emren*†, Sanela Kurtovic, Arna Runarsdottir, Anna-Karin Larsson, and Bengt Mannervik
Department of Biochemistry and Organic Chemistry, Uppsala University, Biomedical Center, Box 576, SE-751 23 Uppsala, Sweden
Communicated by Manfred Eigen, Max Planck Institute for Biophysical Chemistry, Gottingen, Germany, May 17, 2006 (received for reviewDecember 20, 2005)
Molecular evolution is frequently portrayed by structural relat-ionships, but delineation of separate functional species is moreelusive. We have generated enzyme variants by stochastic recom-binations of DNA encoding two homologous detoxication en-zymes, human glutathione transferases M1–1 and M2–2, andexplored their catalytic versatilities. Sampled mutants werescreened for activities with eight alternative substrates, and theactivity fingerprints were subjected to principal component anal-ysis. This phenotype characterization clearly identified at leastthree distributions of substrate selectivity, where one was orthog-onal to those of the parent-like distributions. This approach toevolutionary data mining serves to identify emerging molecularquasi-species and indicates potential trajectories available forfurther protein evolution.
Molecular evolution is based on rearranged polynucleotidesequences and point mutations, which in turn give rise to
novel phenotypes manifested as altered structures and functions.Biological mechanisms of genetic recombinations have counter-parts in DNA shuffling and similar techniques for in vitroevolution (1). For evolution to occur, the mutants arising fromprogenitors undergo a Darwinian selection of the fittest. Thisfunctional filtering of the offspring in combination with struc-tural boundary conditions governs the pathways of evolutionarychange. Directed evolution similarly aims at gratifying qualitiessuch as enhanced catalytic efficiency or increased thermalstability (2). Theoretical and experimental studies indicate thatevolution operates on ensembles of mutants with a stochasticdistribution of structural and functional properties rather thanon single individuals that fit the prevailing conditions. Theseevolving units can be considered molecular ‘‘quasi-species’’ (3).Here, we show how such divergent subpopulations can beidentified by screening and analysis of functional data by mul-tivariate methods, illustrating the emergence of new distribu-tions of functional properties in enzyme evolution.
We approached molecular evolution by analyzing a library ofenzyme variants obtained by recombination of DNA from twohomologous glutathione transferases, GST M1–1 and GST M2–2(4). The GSTs belong to a large family of enzymes that catalyzethe conjugation of the nucleophilic tripeptide glutathione with awide variety of genotoxic substrates. These conjugation reactionsare prominent in the cellular inactivation of electrophilic com-pounds and promote the excretion of toxicants (5). Facileadaptation of substrate selectivities would appear to have selec-tive advantage in particular for enzymes such as GSTs, whichmount a protective response to a wide variety of toxic challenges.
Results and DiscussionEnzyme Variants Represented in a Multidimensional Substrate-ActivitySpace. A library of mutant enzymes was produced by shuffling ofcDNAs encoding human GST M1–1 (M1) and GST M2–2 (M2),which share 84% sequence identity at the protein level but havesignificant functional diversity (6). A set of 384 randomly chosen
clones of GST variants and the two parent enzymes wereexpressed individually in Escherichia coli. The multidimensionalcatalytic activities in the bacterial lysates were examined witheight substrates (Fig. 1) that undergo various alternative chem-ical transformations, representing both substitution and additionreactions. The set of kinetic data were explored by principalcomponent analysis (PCA). The PCA involves transformation ofthe eight-dimensional substrate-activity space such that the firstprincipal component (PC1) describes the direction of largestvariance of the data. PCs of higher order successively charac-terize the subsequent directions of variance orthogonal to theprevious ones (7). The analysis yields a total of eight PCs, ofwhich the major contributors to functional diversity, PC1–PC3,were examined in this paper.
Molecular Quasi-Species Were Revealed by Principal ComponentAnalysis. Three distinct distributions, or quasi-species, were iden-tified by PCA of the library: M1-like, M2-like, and a noveldistribution of mutants. To begin with, the major part (77%) ofthe variance in the data set, as expressed by PC1 and PC2 (Fig.2A), is due to diversity in total activity as well as to combinationsof the multivariate properties of the parents M1 and M2. PC1 isapparently the resultant of the ‘‘overall catalytic activity’’ of theGST variants in the library, and all substrates contribute tosimilar extents (the loadings) to this principal component (Figs.2B and 3B). Fig. 3A displays the distribution of the experimentaldata in the substrate-activity space projected onto the PC2�PC1plane, where PC1 demonstrates an increase in enzyme activityfrom left to right. ‘‘Null’’ mutants (black) with insignificantactivities are found to the left, close to the origin. The axis of thesecond largest variance, PC2, is formed mainly by the activitiesthat distinguish the parent enzymes M1 and M2 (Figs. 2B and 3A,and Table 1). The ‘‘signature substrates’’ of M1 and M2 segre-gate in the loading plot of PC2�PC1 (Fig. 3B): NPG, tPBO, andPEITC (prominent with M1) are found in the lower rightquadrant, whereas CDNB and NCH (foremost with M2) arelocated in the upper right quadrant. Mutants with M1-like(colored blue in Fig. 3) and M2-like (colored red in Fig. 3)activity profiles segregate similarly in Fig. 3A.
Examination of PC3, however, revealed a third, emergingdistribution of mutants (colored green in Fig. 3) orthogonal tothe distributions of parent-like GSTs in PC2�PC1 (Fig. 3C). Theloading plots show that EPNP and pNPA are the substratespositively contributing to the PC3 axis (Fig. 3D). In the PC2�PC1plot (Fig. 3A), this third quasi-species is found mainly in theregion between the parent-like groups and in the domain of
Conflict of interest statement: No conflicts declared.
significantly active enzymes. The boundaries of the groups arenot strictly defined, because the functional properties of themutants cannot be expected to have a normal probabilityvariance. It is still clear that at least three distributions exist, inaddition to the null mutants. The contribution of PC3 to the totalvariance is 10.7% in the scree plot (Fig. 2 A). Considering thedominance of the total activity (PC1) and the properties of theparents M1 and M2 (PC2), a value as high as 10.7% underscoresthe importance of this new dimension of the functional space.
The members of the new distribution are distinguished byhaving pronounced changes of their substrate-selectivity profiles(activity fingerprints), such that the activities with some sub-strates typifying the parents M1 and M2 have dwindled. Therebythe substrate selectivity is increased in favor of the substratesEPNP and pNPA over the alternative substrates, in particularover NPG. This is the most prominent feature of the newquasi-species rather than markedly enhanced activities in com-parison with the parent GSTs (Table 1). The new direction ofevolution thus could have escaped detection in a superficialexamination of the experimental values.
Purified Mutants Have Activity Fingerprints Distinct from Those of theParental GSTs. So far, the analysis was based on the activitymeasurements in the soluble fraction of bacterial lysates. In thesesamples, expressivity, stability, and solubility are superimposedon the intrinsic catalytic properties of the mutants. The actualchanges of the specific activities (per milligram of enzyme) weredetermined for two purified variants, designated 342 and 383, inthe diverging quasi-species (green in Fig. 3). By and large, the
Fig. 1. Molecular structures of eight substrates used in functional screeningof the GST variant library. The substrates are p-nitrophenyl acetate (pNPA),epoxy-3-(4-nitrophenoxy)-propane (EPNP), trans-4-phenyl-3-buten-2-one(tPBO), phenethyl isothiocyanate (PEITC), 3-(4-nitrophenyl)-glycidol (NPG),monochlorobimane (MCB), 1-chloro-2,4-dinitrobenzene (CDNB), and 1-nitro-1-cyclohexene (NCH). Ellipses mark the functional groups undergoing substi-tution or addition reactions with glutathione.
Fig. 2. Principal component (PC) analysis of an eight-dimensional substrate-activity space defined by 386 enzyme variants. (A) Relative contributions ofthe individual PCs to the total variance, presented as a scree plot. (B) Relativecontributions of original activities to the variance of each individual PC(compare Fig. 3).
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activities of these mutants are similar to those of M1 in substi-tution reactions and similar to M2 in addition reactions (Table1). The differences between the purified parent enzymes andvariants 342 and 383 become obvious by comparison of theactivity fingerprints (Fig. 4) constructed by examining the eight-dimensional activity values as ratios of activities. Indeed, variants342 and 383 display similar activity profiles that both clearlydeviate from those of the parental GSTs. In particular, the ratioof pNPA activity over NPG activity is characteristic of the
purified enzymes of the emerging quasi-species (Fig. 4), asdemonstrated in the loadings of PC3 (Fig. 3D). This findingconfirms the conclusions based on the data obtained withbacterial lysates, where variants 383 and 342 were found in adifferent quadrant than M1 and M2 in the PC3�PC2 plane(Fig. 3C).
When the PCA was continued with principal components ofhigher order, a limited number of ‘‘outliers’’ were identified, butno distribution well populated like the ‘‘green’’ group was found.
Fig. 3. Principal component (PC) analysis of activities of the M1�M2 library presented in two orthogonal plane projections. The distribution of the enzymevariants in activity space is projected onto PC planes in A and C. The contributions of experimental activities to the planes are presented in loading plots B andD, respectively. Analyzed enzyme variants are color-labeled according to their spatial distribution in C, with arbitrary boundaries (see Results and Discussion).In A, black-colored mutants demonstrate low or insignificant activities (‘‘null’’ mutants), whereas red (M2-like) and blue (M1-like) mutants exhibit high overallactivity. In C, the green-colored group diverges as a quasi-species in an activity dimension described by PC3, expanded by relatively high activities with pNPA andEPNP, marked in the loading plots.
Table 1. Specific activities of parental enzymes M1 and M2 together with mutants 342 and383, identified as members of the novel quasi-species in Fig. 3C
The activity ratios between the parent enzymes M1 and M2 show the span of functional differences. Thesubstrates undergo substitution reactions (CDNB, MCB, and pNPA) or addition reactions (NPG, EPNP, tPBO, PEITC,and NCH) with glutathione. Data are means � SD (n � 3), after subtraction of the nonenzymatic reaction rate.
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The ‘‘outlying’’ mutants may be representatives of emergingquasi-species that could have been recognized by a more com-prehensive sampling of the mutant library. For a distribution tomanifest itself, the total population obviously has to exceed aminimum size, which depends on the functional propertiesexamined. Conversely, if fewer clones had been examined, theidentified quasi-species could have remained unnoticed as dis-crete distributions and appeared as some unrelated outliers.Furthermore, our ‘‘screening window’’ was based on a limitednumber of catalytic activities and may have failed to recognizeadditional distributions that could exist, even among the nullindividuals.
Chimeric Structures of the Purified GST Variants. The primarystructures of variants 342 and 383 were deduced from their DNAsequences. Both proteins displayed combinations of proteinsequences from the parental enzymes, as expected for productsof the DNA shuffling. Variant 342 is most closely related to M2showing five cross-overs resulting in the following amino acidsubstitutions in the M2 sequence: Ser16Ala, Thr67Ala,Gln140Glu, Glu165Asp, Arg166Leu, Asn167His, Gln168Arg,and Val169Ile. In addition, variant 342 has one random aminoacid alteration, Gln110Arg. Variant 383 is more closely relatedto M1 showing three cross-overs and introducing only twoM2-specific residues in the M1 sequence, Ala67Thr andSer210Thr. One random amino acid mutation, Arg145Trp, wasdetected in variant 383 as well.
Evolution of Novel Substrate-Selectivity Profiles in Vitro and in Vivo.In Table 1 and Fig. 4, ratios of catalytic activities provide activityfingerprints, which describe the discrimination between alterna-tive substrates. Lunzer et al. (8) recently presented an ‘‘ancientsubstrate-selectivity landscape’’ of one natural enzyme expandedby six active-site mutations. In our study, a landscape arises inmultidimensional substrate-activity space by crossing of DNAsegments from two naturally occurring enzymes (6). HumanGST M1–1 and GST M2–2 are homologous proteins with arecent divergence, presumably involving gene convergence orexon shuffling (9). The present investigation illustrates in thiscontext how novel substrate preferences may emerge as a resultof naturally occurring mechanisms involving gene duplication,DNA recombination, and random point mutations. Thus, our
data indicate evolutionary trajectories available to these impor-tant detoxication enzymes. The extant GSTs have alreadyreached a high level of catalytic efficiency with many substrates,and an altered substrate selectivity may therefore be the mostimportant catalytic property in their further evolution (10).
At the molecular level, our stochastic GST library is primarilyan ensemble of chimeric proteins. An early precedent showingthat protein chimeras may present novel biological activitiesinvolved rationally reconstructed interferons (11). In the case ofGSTs, similar redesigns with functional consequences have alsobeen made (ref. 12 and references therein). These initial con-structs were based on common restriction sites in the recom-bined DNA sequences, which severely limited the possiblerecombinations. With the advent of the PCR (13), followed byDNA shuffling (14) and alternative methods (15), DNA recom-binations are no longer limited by these restrictions in sequencespace. Thus, all naturally occurring genetic recombinations canbe mimicked and possibly surpassed with consequent largelyextended diversity of protein structures and functions.
From the evolutionary point of view it is important to promotemutants that differ significantly in functional profiles from thoseof the parent-like enzymes. Such variants can be expected tohave enhanced potential for development of qualitatively newfunctional properties. In natural systems the selection of molec-ular species is obviously based on a multitude of parameters,including physical properties. Molecular breeding therefore de-pends on ample genetic variability to avoid dead ends in evolu-tionary pathways. In the present case, the ‘‘third’’ distributionhas emerged from the central region of the functional spectrumshaped by the parents. Thus, the progeny have expanded prop-erties that both molecular parents exhibit.
Our study addresses the nature of the evolving unit in molec-ular evolution, which in natural systems is not a single individual,but rather a distribution. The same principle applies to directedevolution in vitro, here applied to the discovery of enzymes withaltered functional properties derived from two distinct parents.Directed evolution operates on a compressed time scale, suchthat all mutants produced up to a given time point are accessiblesimultaneously. We show that PCA of this collection can givesnapshots of emerging distributions with novel catalytic prop-erties. Proper interpretation of PCA data serves to reveal
Fig. 4. Activity fingerprints of purified enzyme variants. Data in Table 1 are illustrated by a radar plot of ratios (logarithmic scale) between specific activitieswith pNPA and alternative substrates divided by corresponding ratios of M1. The polygons of clones 342 (green triangles) and 383 (green circles) are outside therange defined by parents M1 (blue squares) and M2 (red squares). The diverging properties of the mutants show the enhanced substrate selectivity for pNPA,one of the substrates distinguishing the third diverging quasi-species.
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quasi-species fit for functional progression in natural molecularevolution as well as in protein engineering.
Materials and MethodsExpression of GST Mutants in Bacteria. The GST M1�M2 library wascreated by DNA shuffling of cDNA encoding human GST M1–1and GST M2–2 (6). DNA from the library was used to transformE. coli XL1-Blue cells (Stratagene) by electroporation. Trans-formants were allowed to recover in 2TY medium [1.6% (wt/vol)tryptone�1% (wt/vol) yeast extract�0.5% (wt/vol) NaCl] at 37°Cfor 1 h before spreading them on LB-ampicillin plates [1%(wt/vol) tryptone�0.5% yeast extract�1% (wt/vol) NaCl�1.5%bacto agar�100 �g/ml ampicillin]. From the library, 384 cloneswere picked randomly and used to inoculate 2 ml of LB medium[1% (wt/vol) tryptone�0.5% (wt/vol) yeast extract�1% (wt/vol)NaCl] supplemented with 100 �g�ml ampicillin. The bacteriawere grown overnight at 37°C with agitation. The cultures werediluted 100-fold into 10 ml of 2TY medium supplemented asabove. After 2 h at 37°C the production of GST was induced byaddition of isopropyl-�-D-thiogalactopyranoside to a final con-centration of 0.2 mM. The bacteria were grown for an additional16 h before being harvested by centrifugation at 1,500 � g for 10min at 4°C. The pellets were resuspended in 250 �l of 0.10 Msodium phosphate buffer (pH 6.5) supplemented with 0.2 mg�mllysozyme to lyse the cells. The suspension was left on ice for 1 hbefore completing the lysis of the sample by freezing and thawingat �80°C for 10 min and at 37°C for 5 min, respectively,performed three times. After the final thawing, the suspensionswere centrifuged for 30 min at 15,000 � g. The supernatants werecollected and transferred to a 96-well plate and stored at �80°C.
Activity Studies on Bacterial Lysates. The GST activities of thelysates were analyzed with eight alternative substrates. Themeasurements were made at 30°C in microplates on a Spectra-Max Plus384 microplate spectrophotometer (Molecular Devices),except with MCB, which was assayed fluorometrically in amicroplate on a Fluoroskan Ascent (Labsystems) at 23°C (16).All measurements were made in duplicate within 12 h of thawingthe lysates. The volume of lysate used for each substrate wasadjusted to give linear progress curves of the reaction velocity.The activity measurements were performed at 30°C in 0.10 Msodium phosphate buffer at pH 6.5, except for pNPA (17), wherethe measurements were performed at pH 7.0. The assays for
CDNB and EPNP were performed as described by Mannervikand Jemth (18). Standard conditions were applied for substratesNPG (19), tPBO (20), and PEITC (21). The conjugation of 0.050mM NCH with 0.50 mM glutathione was monitored at 280 nmby using an extinction coefficient of 4.2 mM�1�cm�1.
Purification and Characterization of Mutants 342 and 383. Fiftymilliliters of 2TY medium supplemented with 100 �g�ml am-picillin was inoculated with 0.5 ml of overnight culture ofXL1-Blue carrying the chosen clone. Induction and purificationfollowed the protocol of Johansson et al. (22). Wild-type GSTsM1–1 and M2–2 were purified in parallel. The purity of thepurified enzymes was determined as �95% with SDS�PAGE.The protein concentration was determined with the Bio-RadProtein Assay (Bio-Rad). The activity with the fluorogenicsubstrate MCB was calculated by using a calibration curve offluorescence against product concentration.
Functional and Structural Analysis of GST Variants. The multivariateanalysis was performed with SIMCA-P� 10.5 (Umetrics) and STA-TISTICA 7.1 (StatSoft). To maintain the true experimental distri-bution, the collected data were not modified by subtraction ofnonenzymatic reactions. Means of duplicate measurements wereanalyzed. Each set of substrate activity was normalized to unitvariance and mean-centered before analysis. For the activeprotein variants the relative standard deviation was �7% (me-dian of all substrates) in the original measured activities. Struc-tural diversity in the mutant library was examined by DNAsequencing of 31 clones, and amino acid sequences were deducedfor the protein variants (the initiation Met was numbered ‘‘1’’).The occurrence of cross-over points and random point mutationswas in agreement with data presented in Hansson et al. (6),displaying 13 possible recombination sites detected in the proteinsequence and, on average, one additional point mutation. Iden-tical protein variants were colocalized in functional space suchthat one pair was found in the emerging quasi-species and agroup of three was in the M1-like quasi-species. This colocal-ization suggests that experimental variance did not bias theidentification of the quasi-species.
We thank Birgit Olin for advice on protein purification. This work wassupported by the Swedish Research Council, the Swedish Cancer Society,and the Carl Trygger Foundation.
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